生成图片

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=false, openWorldHint=true, idempotentHint=false, so the mutation/external-call profile is covered structurally. The description adds only the endpoint and model families; it says nothing about the fact that the call writes files to disk (output_path/overwrite), incurs cost and latency, or is subject to moderation, which are the traits an agent most needs beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with zero filler, identifying the mechanism and model scope immediately. It is efficient, though short enough that it does not use the freed space for any differentiation or behavioral context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists and the parameter schema is fully documented, so return values and inputs need no explanation. However, for a 12-parameter tool that persists files and has two close siblings, the description omits sibling routing and the file-writing behavior, leaving the definition only minimally complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% across all 12 parameters, including enums and defaults, so the schema carries the parameter burden. The description adds no syntax, format, or constraint detail beyond what the schema already states (e.g., the gpt-image- prefix rule is already in the model field). Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource — generating images through the OpenAI Images API (/v1/images/generations) — and names the supported model families. It is clear on its own but never distinguishes itself from the siblings generate_image_via_responses or edit_image, leaving the agent to infer the boundary.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no statement of when to prefer this tool over generate_image_via_responses or edit_image, no prerequisites, and no exclusions. The only routing signal is the API endpoint, which an agent must interpret itself.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.